Longitudinal Interplay Between Alcohol Use, Mood, and Functioning in Bipolar Spectrum Disorders

This cohort study assesses the implications of alcohol consumption for depression, mania or hypomania, anxiety, and workplace functioning among adults with type I or II bipolar disorder.


Introduction
[3] Although BD and AUD are associated with poor outcomes, 4,5 their co-occurrence may further exacerbate risk. 6,7Yet, current treatments for BD rarely include or consider AUD management, and problematic alcohol use is often excluded in BD trials. 6Consequently, the research informing clinical knowledge lacks representation from nearly half of the study population, and the extent of the interplay between alcohol use and BD symptoms is largely unexplored.
Prior cross-sectional work highlights that co-occurrence of AUD and BD is associated with prolonged alcohol withdrawal, more expensive treatment, decreased functioning, increased suicidality, and increased morbidity. 1,5,8These findings are generally corroborated by longitudinal studies.In a 4-year longitudinal study of BD type I (BDI), a history of AUD was associated with poor recovery after mania. 8In a 5-year follow-up, individuals with BDI and AUD experienced more suicidal behavior and poorer social functioning compared with those without AUD. 9Furthermore, those with BD type II (BDII) and AUD were more likely to have a manic episode and transition to a BDI diagnosis 5 years later, highlighting that co-occurring AUD is associated with worse outcomes of BD regardless of subtype.
Reviews also highlight associations between AUD and more complex (eg, mixed or dysphoric mania 2,10 and rapid cycling 2,[10][11][12] ) and severe mood symptoms, 1,6,7,[13][14][15] the onset of which can be precipitated by alcohol use. 12,16,17Depressive symptoms seem to both precede and occur after alcohol use in BD throughout follow-up periods ranging from 8 months 13 to 10 years. 18The association of anxiety, which affects up to 45% of individuals with BD, 19 with alcohol use in BD has been less studied.Given the bidirectional risk between AUD and anxiety, 20 this gap in the BD literature poses considerable clinical implications.
Despite the literature, it remains unclear how alcohol use fluctuates over time in BD and how longitudinal dynamics interact with proximal changes in depressive, manic or hypomanic, and anxiety symptoms.Examining these dynamics can inform the mechanisms of how alcohol use plays a role in poorer outcomes in BD, when to intervene, and whether alcohol use affects mood symptoms even at subclinical levels.This understanding is critical given that (1) general clinical practices function on the perspective that alcohol is primarily used as self-medication with little longitudinal research to support this viewpoint and (2) extant research has largely focused on co-occurrence of AUD only.
The objective of the present study was to characterize the longitudinal patterns of alcohol use in one of the largest, ongoing cohort studies of BD, the Prechter Longitudinal Study of Bipolar Disorder (PLS-BD), 21,22 and examine the temporal associations among alcohol use, mood, anxiety, and functioning over time.We hypothesized that (1) greater alcohol use is associated with more manic or hypomanic and depressive symptoms, (2) within-person increases in alcohol use are associated with an increase in manic or hypomanic and depressive symptoms at later time points, (3)   within-person worsening of mood is associated with future increase in alcohol use, and (4) withinperson increases in alcohol use are associated with worse functioning.Given the limited research on the association between alcohol use and anxiety in BD, we conducted exploratory analyses to examine these bidirectional associations.in future secondary data analysis.We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
The complete PLS-BD cohort currently consists of individuals enrolled for a median (IQR) of 9 (0-16) years.Enrollment, which started in February 2006, is rolling.The present study analyzed data collected from February 2006 to April 2022.Exclusion criteria were neurological disease and inability to interview without being intoxicated on alcohol or substances.Selected participants were those with a diagnosis of BDI or BDII who had been in the study for at least 5 years (eFigure 1 in Supplement 1).Healthy controls and those with other psychiatric diagnoses were not included in the present study.Self-reported race and ethnicity data were collected to enhance the generalizability of the PLS-BD findings to multiple identities.Diagnosis was assessed using the Diagnostic Interview for Genetic Studies. 23A team of at least 2 doctoral-level psychologists or psychiatrists (including S.H.S., M.G.M., I.F.T.) confirmed the diagnoses using Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) criteria and available medical and treatment history.

Materials and Procedures
Comprehensive information on the study procedures for participants in the PLS-BD is available elsewhere. 21,22All self-reported measures for the PLS-BD were collected digitally using a secure, web-based research study platform (REDCap; Vanderbilt University). 24,25Materials and procedures for the current investigation are detailed herein.
Alcohol consumption, drinking behavior, and alcohol-related problems were measured with the Alcohol Use Disorders Identification Test (AUDIT) 26 at baseline and every 6 months.The AUDIT score range is from 0 to 40, with 8 or higher indicating AUD is highly probable; 8 to 14 indicating hazardous or harmful drinking; and 15 to 40 indicating severe drinking or dependence.Internal consistency, calculated using Cronbach α, was excellent (α = .90).Participants completed 59% of delivered AUDIT assessments.
The Life Functioning Questionnaire (LFQ), 27 developed to assess life functioning in individuals with BD, was administered at baseline and every 2 months.The LFQ measures functioning over the past month in 4 domains: leisure time with friends (LFQ friend); leisure time with family (LFQ family); duties at work, school, or activity center (LFQ work); and duties at home (LFQ home).Items in the questionnaire are rated using a Likert scale: 0 (does not spend a substantial amount of time in domain), 1 (no problems), 2 (mild problems), 3 (moderate problems), and 4 (severe problems).These scores are averaged across each of the 4 domains.Internal consistency for each LFQ subscale was good (α = .77-.84).Participants completed 57% of delivered LFQ assessments.

Statistical Analysis
Summary statistics were estimated using the psych package in RStudio, V.2022.02.0+443 (RStudio). 31To model the temporal dynamics among alcohol use, mood, and functioning, we used Dynamic Structural Equation Modeling (DSEM) 32 to fit multivariable, multilevel first-order vector autoregressive models in MPlus, version 8.1 (MPlus).A strength of DSEM is its ability to handle missingness in longitudinal data: DSEM uses the Kalman filter approach, which estimates a missing observation at time t based on its lagged observation. 33Details regarding DSEM are provided in
Demographic statistics for the entire cohort are available elsewhere. 22Herein we report the results from the conditional models, including planned covariates.

Affective Symptoms and Alcohol Use
A person reporting alcohol use above their own mean amount tended to experience more depressive symptoms at the next time point, but increased depressive symptoms were not associated with greater subsequent alcohol use (β = 0.04; 95% CrI, 0.01-0.07)(Figure 2).This cross-lagged association was not as pronounced for those taking antipsychotics compared with those not taking antipsychotics (β = -0.21;95% CrI, -0.39 to -0.02) (Table 1).Previous depression symptoms were associated with 11.0% of the variance in alcohol use after 6 months, whereas alcohol use was

JAMA Network Open | Psychiatry
Interplay Between Alcohol Use, Mood, and Functioning in Bipolar Spectrum Disorders associated with 34.0% of the variance in depression symptoms after 6 months.Regarding mania or hypomania, alcohol use exceeding one's own mean amount was associated with an increase in manic or hypomanic symptoms at the next time point, but not vice versa (β = 0.04; 95% CrI, 0.01-0.07])(Figure 2).Those with BDII showed a more pronounced cross-lagged association between alcohol use and manic or hypomanic symptoms compared with those with BDI (β = 0.16; 95% CrI, 0.02-0.30)(Table 1).Manic or hypomanic symptoms were associated with 11.0% of the variance in alcohol use after 6 months, whereas alcohol use was associated with 18.0% of the variance in manic or hypomanic symptoms after 6 months.Regarding anxiety, no within-person associations emerged with alcohol use, regardless of covariates (eFigure 3 in Supplement 1; Table 1).

Functioning and Alcohol Use
A person reporting alcohol use above their own mean amount tended to experience a decrease in work functioning at the next time point, but not vice versa (β = 0.03; 95% CrI, 0.00-0.06)(Figure 3).This association was more pronounced in BDII than BDI (β = 0.26; 95% CrI, 0.06-0.45)and for individuals using mood stabilizers (β = 0.38; 95% CrI, 0.03-0.62),and it was less pronounced for individuals using antidepressants (β = −0.29;95% CrI, −0.51 to −0.01) (Table 2).Given the large and near-0 95% CrI for the latter finding, caution should be exercised about overinterpreting the result.Work functioning was associated with 17.0% of the variance in alcohol use after 6 months, whereas alcohol use was associated with 40.0% of the variance in work functioning after 6 months.Abbreviations: ASRM, Altman Self-Rating Mania Scale; BD, bipolar disorder; CrI, credibility interval.a Estimated means ( 95% CrIs) represent the mean of that DSEM parameter across the sample.Estimates β (95% CrIs) include standardized estimates and 95% CrIs.For example, patients using anticonvulsant mood stabilizers had a mean depression score that was 0.16 (95% CrI, −0.26 to −0.04) SDs below the estimated mean (8.15

Discussion
Consistent with our hypotheses, more problematic drinking was associated with depression and mania or hypomania later.Increased depression and mania or hypomania was not associated with greater subsequent alcohol use.Furthermore, greater problematic alcohol use was associated with worse functioning at work but was not associated with functioning in other domains later.Taken together, these results highlight the role that alcohol use may play in ongoing mood instability and functional impairment in BD.
The findings regarding the temporal association of depression and mania or hypomania with alcohol use are inconsistent with the self-medication hypothesis of addiction. 34The self-medication A and C, Dashed lines represent noncredible differences (95% CrI contains 0), and solid lines represent credible differences (95% CrI does not include 0).t indicates time; t-1, time -1 observation; AA , autocorrelation of Alcohol Use Disorders Identification Test (AUDIT); ASRM→AUDIT , cross-lagged association between Altman Self-Rating Mania Scale (ASRM) and AUDIT at the next time point; AUDIT→ASRM , cross-lagged association between AUDIT and ASRM at the next time point; AUDIT→PHQ-9 , cross-lagged association between AUDIT and 9-Item Patient Health Questionnaire (PHQ-9) at the next time point; MM , autocorrelation of ASRM; PHQ-9→AUDIT , cross-lagged association between PHQ-9 and AUDIT at the next time point; PP , autocorrelation of PHQ-9; log(π ASRM ), within-person variability in ASRM; log(π AUDIT ), within-person variability in AUDIT; log(π PHQ-9 ), within-person variability in PHQ-9.B and C, Each tan line represents a participant in the study.The blue solid line represents the group mean with SE around the mean.
hypothesis posits that addiction is associated with use of substances to mitigate distressing symptoms.Thus, in individuals with psychiatric disorders, the behavioral motivator of substance use may be to reduce or increase specific emotional states. 35Alcohol, given its fast action and temporary relief as a central nervous system depressant, may be particularly prone to such use.By this logic, we would have expected that increased affective symptoms would have been associated with greater alcohol use over time.However, we found that the opposite (ie, increased problematic alcohol use) was associated with subsequent worsening of depressive and manic or hypomanic symptoms.Notably, there were no significant individual differences in this random effect, indicating that this temporal pattern was consistent across individuals.
We also found diagnostic differences in alcohol use.Individuals with BDII exhibited higher autocorrelation in AUDIT scores, indicating that greater alcohol use in this group was more likely to persist over time.These individuals also exhibited more pronounced worsening of workplace function following a period of increased problematic alcohol use.Increased manic or hypomanic symptoms after increased alcohol use were more pronounced in BDII than in BDI.Prior literature has linked greater alcohol use to mania or hypomania in BD in combined samples, 12,36,37 but these studies did not examine whether these associations differed across subtypes.By conducting this delineated we provide insights into subtype-specific dynamics of alcohol use and mania or hypomania.However, the diagnostic findings seemingly contradict earlier studies that linked co-occurring alcohol use with BDI to a worse illness course than with BDII. 9,12While these previous studies assessed illness course in different ways, the present study of autocorrelation of alcohol use and functioning focused on previously unexplored domains.
Medication use emerged as a factor associated with the temporal dynamics of alcohol use.Individuals using antipsychotics reported lower mean AUDIT scores, less variable alcohol use, and a lower likelihood of depression playing a role in future alcohol use.Individuals using mood stabilizers exhibited more pronounced worsening of work functioning after a period of greater problematic alcohol use.Benzodiazepine use was associated with a lower autocorrelation in alcohol use but higher variability in depression and more manic or hypomanic symptoms.In contrast, individuals using antidepressants tended to have greater variability in alcohol use.Notably, these results should not be interpreted as causal as they were simply associations.It is plausible that persons with co-occurring BD and alcohol use are more likely to be prescribed antipsychotics or that individuals A, Dashed lines represent noncredible differences (95% credible interval [CrI] contains 0), and solid lines represent credible differences (95% CrI does not include 0).Abbreviations: BD, bipolar disorder; CrI, credibility interval.a Estimated means (95% CrIs) represent the mean of that DSEM parameter across the sample.Estimated β (95% CrIs) include standardized estimates and 95% CrIs.For example, patients using antipsychotic mood stabilizers had a mean Alcohol Use Disorders Identification Test score that was −0.20 (95% CrI, −0.31 to −0.07) SD below the estimated mean (2.32 ) log(π AUDIT ), within-person variability in AUDIT over time.All other models had the following parameters: MM , autocorrelation of ASRM; GG , autocorrelation of GAD-7; FF , autocorrelation of LFQ family (in LFQ family model); FF , autocorrelation of LFQ friend (in LFQ friend model); WW , autocorrelation of LFQ work; and HH , autocorrelation of LFQ home.

1
Within-person parameters estimated in the conditional DSEM with PHQ-9 and AUDIT measures A A patient's cross-lagged regression between AUDIT and PHQ-9 (left) and between PHQ-9 and AUDIT (right) at the next time point

1 A
patient's cross-lagged regression between AUDIT and ASRM (left) and between ASRM and AUDIT (right) at the next time point parameters estimated in the conditional DSEM with ASRM and AUDIT measures

Figure 3 .
Figure 3. Conditional Dynamic Structural Equation Modeling (DSEM) for Life Functioning Within-person parameters estimated in the conditional DSEM with LFQ work and AUDIT measuresA A patient's cross-lagged regression between AUDIT and LFQ work (left) and between LFQ work and AUDIT (right) at the next time point

Table 1 .
Conditional Dynamic Structural Equation Modeling (DSEM) for Affective Measures a AUDIT ) are not repeated in each model to reduce redundancy in the table.No within-person associations emerged between AUDIT scores and the family, friend, or home functioning domains (eFigure 4 in Supplement 1).
b See the Methods section for details on the parameters for the variables.cThe95% CrI does not include 0, suggesting that the association is credible.JAMA Network Open | PsychiatryInterplay Between Alcohol Use, Mood, and Functioning in Bipolar Spectrum Disorders JAMA Network Open.2024;7(6):e2415295.doi:10.1001/jamanetworkopen.2024.15295(Reprinted) June 7, 2024 6/14 Downloaded from jamanetwork.comby guest on 06/09/2024 t indicates time; t-1, time -1 observation; AA , autocorrelation of Alcohol Use Disorders Identification Test (AUDIT); AUDIT→Work , cross-lagged association between AUDIT and Life Functioning Questionnaire (LFQ) work at the next time point; Work→AUDIT , cross-lagged association between LFQ work and AUDIT at the next time point; log(π AUDIT ) , within-person variability in AUDIT; log(π Work ), within-person variability of LFQ work; WW , autocorrelation of LFQ work.B, Each tan line represents a participant in the study.The blue solid line represents the group mean with SE around the mean.

Table 2 .
Conditional Dynamic Structural Equation Modeling (DSEM) for Functioning Measures a ; 95% CrI, 1.58-3.06).Note that μ AUDIT , AA , and log(π AUDIT ) are not repeated in each model to reduce redundancy in the table.Unconditional DSEM Model: GAD7 and AUDIT eTable 6. Unconditional DSEM Model: LFQ Family and AUDIT eTable 7. Unconditional DSEM Model: LFQ Friend and AUDIT eTable 8. Unconditional DSEM Model: LFQ Family and AUDIT eTable 9. Unconditional DSEM Model: LFQ Work and AUDIT eFigure 3. Conditional DSEM Model for GAD7 and AUDIT eFigure 4. Conditional DSEM Model for LFQ Family, Friend, and Home with AUDIT b See the Methods section for details on the parameters for the variables.c The 95% CrI does not include 0, suggesting that the association is credible.eTable 5.